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Paper Citation Record · LEDGER

AGaLiTe: Approximate Gated Linear Transformers for Online Reinforcement Learning

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2310.15719.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2310.15719 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T14:58:28.372580Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-15T01:15:14.166409Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 82b065f2-d74a-4973-b409-20c358d8f77f · inbound

Gated Linear Attention Transformers with Hardware-Efficient Training cites this paper.

Gated Linear Attention Transformers with Hardware-Efficient Training AGaLiTe: Approximate Gated Linear Transformers for Online Reinforcement Learning

Reference 68

Resolution
verified exact
arxiv_id, observed 2026-05-15T01:15:14.167827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-15T01:15:13.991219Z digest=sha256:ce7418b221f494235d6a15e6e2eaba2becefb91eb3bc455c6b133c807c9f66f3

Observation 55091fc3-93a7-4ee2-9984-e9de5b8d0c2b · inbound

ReGLA: Refining Gated Linear Attention cites this paper.

ReGLA: Refining Gated Linear Attention AGaLiTe: Approximate Gated Linear Transformers for Online Reinforcement Learning

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-09T14:58:28.372580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T14:58:28.372580Z digest=sha256:9bf2999abf5ecd88b524fcf43e5ca298343eea7425a01cbe33ba5d05c95cd3c7